Tag Archives: Silicon Valley

Vector Institute and Canada’s artificial intelligence sector

On the heels of the March 22, 2017 federal budget announcement of $125M for a Pan-Canadian Artificial Intelligence Strategy, the University of Toronto (U of T) has announced the inception of the Vector Institute for Artificial Intelligence in a March 28, 2017 news release by Jennifer Robinson (Note: Links have been removed),

A team of globally renowned researchers at the University of Toronto is driving the planning of a new institute staking Toronto’s and Canada’s claim as the global leader in AI.

Geoffrey Hinton, a University Professor Emeritus in computer science at U of T and vice-president engineering fellow at Google, will serve as the chief scientific adviser of the newly created Vector Institute based in downtown Toronto.

“The University of Toronto has long been considered a global leader in artificial intelligence research,” said U of T President Meric Gertler. “It’s wonderful to see that expertise act as an anchor to bring together researchers, government and private sector actors through the Vector Institute, enabling them to aim even higher in leading advancements in this fast-growing, critical field.”

As part of the Government of Canada’s Pan-Canadian Artificial Intelligence Strategy, Vector will share $125 million in federal funding with fellow institutes in Montreal and Edmonton. All three will conduct research and secure talent to cement Canada’s position as a world leader in AI.

In addition, Vector is expected to receive funding from the Province of Ontario and more than 30 top Canadian and global companies eager to tap this pool of talent to grow their businesses. The institute will also work closely with other Ontario universities with AI talent.

(See my March 24, 2017 posting; scroll down about 25% for the science part, including the Pan-Canadian Artificial Intelligence Strategy of the budget.)

Not obvious in last week’s coverage of the Pan-Canadian Artificial Intelligence Strategy is that the much lauded Hinton has been living in the US and working for Google. These latest announcements (Pan-Canadian AI Strategy and Vector Institute) mean that he’s moving back.

A March 28, 2017 article by Kate Allen for TorontoStar.com provides more details about the Vector Institute, Hinton, and the Canadian ‘brain drain’ as it applies to artificial intelligence, (Note:  A link has been removed)

Toronto will host a new institute devoted to artificial intelligence, a major gambit to bolster a field of research pioneered in Canada but consistently drained of talent by major U.S. technology companies like Google, Facebook and Microsoft.

The Vector Institute, an independent non-profit affiliated with the University of Toronto, will hire about 25 new faculty and research scientists. It will be backed by more than $150 million in public and corporate funding in an unusual hybridization of pure research and business-minded commercial goals.

The province will spend $50 million over five years, while the federal government, which announced a $125-million Pan-Canadian Artificial Intelligence Strategy in last week’s budget, is providing at least $40 million, backers say. More than two dozen companies have committed millions more over 10 years, including $5 million each from sponsors including Google, Air Canada, Loblaws, and Canada’s five biggest banks [Bank of Montreal (BMO). Canadian Imperial Bank of Commerce ({CIBC} President’s Choice Financial},  Royal Bank of Canada (RBC), Scotiabank (Tangerine), Toronto-Dominion Bank (TD Canada Trust)].

The mode of artificial intelligence that the Vector Institute will focus on, deep learning, has seen remarkable results in recent years, particularly in image and speech recognition. Geoffrey Hinton, considered the “godfather” of deep learning for the breakthroughs he made while a professor at U of T, has worked for Google since 2013 in California and Toronto.

Hinton will move back to Canada to lead a research team based at the tech giant’s Toronto offices and act as chief scientific adviser of the new institute.

Researchers trained in Canadian artificial intelligence labs fill the ranks of major technology companies, working on tools like instant language translation, facial recognition, and recommendation services. Academic institutions and startups in Toronto, Waterloo, Montreal and Edmonton boast leaders in the field, but other researchers have left for U.S. universities and corporate labs.

The goals of the Vector Institute are to retain, repatriate and attract AI talent, to create more trained experts, and to feed that expertise into existing Canadian companies and startups.

Hospitals are expected to be a major partner, since health care is an intriguing application for AI. Last month, researchers from Stanford University announced they had trained a deep learning algorithm to identify potentially cancerous skin lesions with accuracy comparable to human dermatologists. The Toronto company Deep Genomics is using deep learning to read genomes and identify mutations that may lead to disease, among other things.

Intelligent algorithms can also be applied to tasks that might seem less virtuous, like reading private data to better target advertising. Zemel [Richard Zemel, the institute’s research director and a professor of computer science at U of T] says the centre is creating an ethics working group [emphasis mine] and maintaining ties with organizations that promote fairness and transparency in machine learning. As for privacy concerns, “that’s something we are well aware of. We don’t have a well-formed policy yet but we will fairly soon.”

The institute’s annual funding pales in comparison to the revenues of the American tech giants, which are measured in tens of billions. The risk the institute’s backers are taking is simply creating an even more robust machine learning PhD mill for the U.S.

“They obviously won’t all stay in Canada, but Toronto industry is very keen to get them,” Hinton said. “I think Trump might help there.” Two researchers on Hinton’s new Toronto-based team are Iranian, one of the countries targeted by U.S. President Donald Trump’s travel bans.

Ethics do seem to be a bit of an afterthought. Presumably the Vector Institute’s ‘ethics working group’ won’t include any regular folks. Is there any thought to what the rest of us think about these developments? As there will also be some collaboration with other proposed AI institutes including ones at the University of Montreal (Université de Montréal) and the University of Alberta (Kate McGillivray’s article coming up shortly mentions them), might the ethics group be centered in either Edmonton or Montreal? Interestingly, two Canadians (Timothy Caulfield at the University of Alberta and Eric Racine at Université de Montréa) testified at the US Commission for the Study of Bioethical Issues Feb. 10 – 11, 2014 meeting, the Brain research, ethics, and nanotechnology. Still speculating here but I imagine Caulfield and/or Racine could be persuaded to extend their expertise in ethics and the human brain to AI and its neural networks.

Getting back to the topic at hand the ‘AI sceneCanada’, Allen’s article is worth reading in its entirety if you have the time.

Kate McGillivray’s March 29, 2017 article for the Canadian Broadcasting Corporation’s (CBC) news online provides more details about the Canadian AI situation and the new strategies,

With artificial intelligence set to transform our world, a new institute is putting Toronto to the front of the line to lead the charge.

The Vector Institute for Artificial Intelligence, made possible by funding from the federal government revealed in the 2017 budget, will move into new digs in the MaRS Discovery District by the end of the year.

Vector’s funding comes partially from a $125 million investment announced in last Wednesday’s federal budget to launch a pan-Canadian artificial intelligence strategy, with similar institutes being established in Montreal and Edmonton.

“[A.I.] cuts across pretty well every sector of the economy,” said Dr. Alan Bernstein, CEO and president of the Canadian Institute for Advanced Research, the organization tasked with administering the federal program.

“Silicon Valley and England and other places really jumped on it, so we kind of lost the lead a little bit. I think the Canadian federal government has now realized that,” he said.

Stopping up the brain drain

Critical to the strategy’s success is building a homegrown base of A.I. experts and innovators — a problem in the last decade, despite pioneering work on so-called “Deep Learning” by Canadian scholars such as Yoshua Bengio and Geoffrey Hinton, a former University of Toronto professor who will now serve as Vector’s chief scientific advisor.

With few university faculty positions in Canada and with many innovative companies headquartered elsewhere, it has been tough to keep the few graduates specializing in A.I. in town.

“We were paying to educate people and shipping them south,” explained Ed Clark, chair of the Vector Institute and business advisor to Ontario Premier Kathleen Wynne.

The existence of that “fantastic science” will lean heavily on how much buy-in Vector and Canada’s other two A.I. centres get.

Toronto’s portion of the $125 million is a “great start,” said Bernstein, but taken alone, “it’s not enough money.”

“My estimate of the right amount of money to make a difference is a half a billion or so, and I think we will get there,” he said.

Jessica Murphy’s March 29, 2017 article for the British Broadcasting Corporation’s (BBC) news online offers some intriguing detail about the Canadian AI scene,

Canadian researchers have been behind some recent major breakthroughs in artificial intelligence. Now, the country is betting on becoming a big player in one of the hottest fields in technology, with help from the likes of Google and RBC [Royal Bank of Canada].

In an unassuming building on the University of Toronto’s downtown campus, Geoff Hinton laboured for years on the “lunatic fringe” of academia and artificial intelligence, pursuing research in an area of AI called neural networks.

Also known as “deep learning”, neural networks are computer programs that learn in similar way to human brains. The field showed early promise in the 1980s, but the tech sector turned its attention to other AI methods after that promise seemed slow to develop.

“The approaches that I thought were silly were in the ascendancy and the approach that I thought was the right approach was regarded as silly,” says the British-born [emphasis mine] professor, who splits his time between the university and Google, where he is a vice-president of engineering fellow.

Neural networks are used by the likes of Netflix to recommend what you should binge watch and smartphones with voice assistance tools. Google DeepMind’s AlphaGo AI used them to win against a human in the ancient game of Go in 2016.

Foteini Agrafioti, who heads up the new RBC Research in Machine Learning lab at the University of Toronto, said those recent innovations made AI attractive to researchers and the tech industry.

“Anything that’s powering Google’s engines right now is powered by deep learning,” she says.

Developments in the field helped jumpstart innovation and paved the way for the technology’s commercialisation. They also captured the attention of Google, IBM and Microsoft, and kicked off a hiring race in the field.

The renewed focus on neural networks has boosted the careers of early Canadian AI machine learning pioneers like Hinton, the University of Montreal’s Yoshua Bengio, and University of Alberta’s Richard Sutton.

Money from big tech is coming north, along with investments by domestic corporations like banking multinational RBC and auto parts giant Magna, and millions of dollars in government funding.

Former banking executive Ed Clark will head the institute, and says the goal is to make Toronto, which has the largest concentration of AI-related industries in Canada, one of the top five places in the world for AI innovation and business.

The founders also want it to serve as a magnet and retention tool for top talent aggressively head-hunted by US firms.

Clark says they want to “wake up” Canadian industry to the possibilities of AI, which is expected to have a massive impact on fields like healthcare, banking, manufacturing and transportation.

Google invested C$4.5m (US$3.4m/£2.7m) last November [2016] in the University of Montreal’s Montreal Institute for Learning Algorithms.

Microsoft is funding a Montreal startup, Element AI. The Seattle-based company also announced it would acquire Montreal-based Maluuba and help fund AI research at the University of Montreal and McGill University.

Thomson Reuters and General Motors both recently moved AI labs to Toronto.

RBC is also investing in the future of AI in Canada, including opening a machine learning lab headed by Agrafioti, co-funding a program to bring global AI talent and entrepreneurs to Toronto, and collaborating with Sutton and the University of Alberta’s Machine Intelligence Institute.

Canadian tech also sees the travel uncertainty created by the Trump administration in the US as making Canada more attractive to foreign talent. (One of Clark’s the selling points is that Toronto as an “open and diverse” city).

This may reverse the ‘brain drain’ but it appears Canada’s role as a ‘branch plant economy’ for foreign (usually US) companies could become an important discussion once more. From the ‘Foreign ownership of companies of Canada’ Wikipedia entry (Note: Links have been removed),

Historically, foreign ownership was a political issue in Canada in the late 1960s and early 1970s, when it was believed by some that U.S. investment had reached new heights (though its levels had actually remained stable for decades), and then in the 1980s, during debates over the Free Trade Agreement.

But the situation has changed, since in the interim period Canada itself became a major investor and owner of foreign corporations. Since the 1980s, Canada’s levels of investment and ownership in foreign companies have been larger than foreign investment and ownership in Canada. In some smaller countries, such as Montenegro, Canadian investment is sizable enough to make up a major portion of the economy. In Northern Ireland, for example, Canada is the largest foreign investor. By becoming foreign owners themselves, Canadians have become far less politically concerned about investment within Canada.

Of note is that Canada’s largest companies by value, and largest employers, tend to be foreign-owned in a way that is more typical of a developing nation than a G8 member. The best example is the automotive sector, one of Canada’s most important industries. It is dominated by American, German, and Japanese giants. Although this situation is not unique to Canada in the global context, it is unique among G-8 nations, and many other relatively small nations also have national automotive companies.

It’s interesting to note that sometimes Canadian companies are the big investors but that doesn’t change our basic position. And, as I’ve noted in other postings (including the March 24, 2017 posting), these government investments in science and technology won’t necessarily lead to a move away from our ‘branch plant economy’ towards an innovative Canada.

You can find out more about the Vector Institute for Artificial Intelligence here.

BTW, I noted that reference to Hinton as ‘British-born’ in the BBC article. He was educated in the UK and subsidized by UK taxpayers (from his Wikipedia entry; Note: Links have been removed),

Hinton was educated at King’s College, Cambridge graduating in 1970, with a Bachelor of Arts in experimental psychology.[1] He continued his study at the University of Edinburgh where he was awarded a PhD in artificial intelligence in 1977 for research supervised by H. Christopher Longuet-Higgins.[3][12]

It seems Canadians are not the only ones to experience  ‘brain drains’.

Finally, I wrote at length about a recent initiative taking place between the University of British Columbia (Vancouver, Canada) and the University of Washington (Seattle, Washington), the Cascadia Urban Analytics Cooperative in a Feb. 28, 2017 posting noting that the initiative is being funded by Microsoft to the tune $1M and is part of a larger cooperative effort between the province of British Columbia and the state of Washington. Artificial intelligence is not the only area where US technology companies are hedging their bets (against Trump’s administration which seems determined to terrify people from crossing US borders) by investing in Canada.

For anyone interested in a little more information about AI in the US and China, there’s today’s (March 31, 2017)earlier posting: China, US, and the race for artificial intelligence research domination.

China, US, and the race for artificial intelligence research domination

John Markoff and Matthew Rosenberg have written a fascinating analysis of the competition between US and China regarding technological advances, specifically in the field of artificial intelligence. While the focus of the Feb. 3, 2017 NY Times article is military, the authors make it easy to extrapolate and apply the concepts to other sectors,

Robert O. Work, the veteran defense official retained as deputy secretary by President Trump, calls them his “A.I. dudes.” The breezy moniker belies their serious task: The dudes have been a kitchen cabinet of sorts, and have advised Mr. Work as he has sought to reshape warfare by bringing artificial intelligence to the battlefield.

Last spring, he asked, “O.K., you guys are the smartest guys in A.I., right?”

No, the dudes told him, “the smartest guys are at Facebook and Google,” Mr. Work recalled in an interview.

Now, increasingly, they’re also in China. The United States no longer has a strategic monopoly on the technology, which is widely seen as the key factor in the next generation of warfare.

The Pentagon’s plan to bring A.I. to the military is taking shape as Chinese researchers assert themselves in the nascent technology field. And that shift is reflected in surprising commercial advances in artificial intelligence among Chinese companies. [emphasis mine]

Having read Marshal McLuhan (de rigeur for any Canadian pursuing a degree in communications [sociology-based] anytime from the 1960s into the late 1980s [at least]), I took the movement of technology from military research to consumer applications as a standard. Television is a classic example but there are many others including modern plastic surgery. The first time, I encountered the reverse (consumer-based technology being adopted by the military) was in a 2004 exhibition “Massive Change: The Future of Global Design” produced by Bruce Mau for the Vancouver (Canada) Art Gallery.

Markoff and Rosenberg develop their thesis further (Note: Links have been removed),

Last year, for example, Microsoft researchers proclaimed that the company had created software capable of matching human skills in understanding speech.

Although they boasted that they had outperformed their United States competitors, a well-known A.I. researcher who leads a Silicon Valley laboratory for the Chinese web services company Baidu gently taunted Microsoft, noting that Baidu had achieved similar accuracy with the Chinese language two years earlier.

That, in a nutshell, is the challenge the United States faces as it embarks on a new military strategy founded on the assumption of its continued superiority in technologies such as robotics and artificial intelligence.

First announced last year by Ashton B. Carter, President Barack Obama’s defense secretary, the “Third Offset” strategy provides a formula for maintaining a military advantage in the face of a renewed rivalry with China and Russia.

As consumer electronics manufacturing has moved to Asia, both Chinese companies and the nation’s government laboratories are making major investments in artificial intelligence.

The advance of the Chinese was underscored last month when Qi Lu, a veteran Microsoft artificial intelligence specialist, left the company to become chief operating officer at Baidu, where he will oversee the company’s ambitious plan to become a global leader in A.I.

The authors note some recent military moves (Note: Links have been removed),

In August [2016], the state-run China Daily reported that the country had embarked on the development of a cruise missile system with a “high level” of artificial intelligence. The new system appears to be a response to a missile the United States Navy is expected to deploy in 2018 to counter growing Chinese military influence in the Pacific.

Known as the Long Range Anti-Ship Missile, or L.R.A.S.M., it is described as a “semiautonomous” weapon. According to the Pentagon, this means that though targets are chosen by human soldiers, the missile uses artificial intelligence technology to avoid defenses and make final targeting decisions.

The new Chinese weapon typifies a strategy known as “remote warfare,” said John Arquilla, a military strategist at the Naval Post Graduate School in Monterey, Calif. The idea is to build large fleets of small ships that deploy missiles, to attack an enemy with larger ships, like aircraft carriers.

“They are making their machines more creative,” he said. “A little bit of automation gives the machines a tremendous boost.”

Whether or not the Chinese will quickly catch the United States in artificial intelligence and robotics technologies is a matter of intense discussion and disagreement in the United States.

Markoff and Rosenberg return to the world of consumer electronics as they finish their article on AI and the military (Note: Links have been removed),

Moreover, while there appear to be relatively cozy relationships between the Chinese government and commercial technology efforts, the same cannot be said about the United States. The Pentagon recently restarted its beachhead in Silicon Valley, known as the Defense Innovation Unit Experimental facility, or DIUx. It is an attempt to rethink bureaucratic United States government contracting practices in terms of the faster and more fluid style of Silicon Valley.

The government has not yet undone the damage to its relationship with the Valley brought about by Edward J. Snowden’s revelations about the National Security Agency’s surveillance practices. Many Silicon Valley firms remain hesitant to be seen as working too closely with the Pentagon out of fear of losing access to China’s market.

“There are smaller companies, the companies who sort of decided that they’re going to be in the defense business, like a Palantir,” said Peter W. Singer, an expert in the future of war at New America, a think tank in Washington, referring to the Palo Alto, Calif., start-up founded in part by the venture capitalist Peter Thiel. “But if you’re thinking about the big, iconic tech companies, they can’t become defense contractors and still expect to get access to the Chinese market.”

Those concerns are real for Silicon Valley.

If you have the time, I recommend reading the article in its entirety.

Impact of the US regime on thinking about AI?

A March 24, 2017 article by Daniel Gross for Slate.com hints that at least one high level offician in the Trump administration may be a little naïve in his understanding of AI and its impending impact on US society (Note: Links have been removed),

Treasury Secretary Steven Mnuchin is a sharp guy. He’s a (legacy) alumnus of Yale and Goldman Sachs, did well on Wall Street, and was a successful movie producer and bank investor. He’s good at, and willing to, put other people’s money at risk alongside some of his own. While he isn’t the least qualified person to hold the post of treasury secretary in 2017, he’s far from the best qualified. For in his 54 years on this planet, he hasn’t expressed or displayed much interest in economic policy, or in grappling with the big picture macroeconomic issues that are affecting our world. It’s not that he is intellectually incapable of grasping them; they just haven’t been in his orbit.

Which accounts for the inanity he uttered at an Axios breakfast Friday morning about the impact of artificial intelligence on jobs.

“it’s not even on our radar screen…. 50-100 more years” away, he said. “I’m not worried at all” about robots displacing humans in the near future, he said, adding: “In fact I’m optimistic.”

A.I. is already affecting the way people work, and the work they do. (In fact, I’ve long suspected that Mike Allen, Mnuchin’s Axios interlocutor, is powered by A.I.) I doubt Mnuchin has spent much time in factories, for example. But if he did, he’d see that machines and software are increasingly doing the work that people used to do. They’re not just moving goods through an assembly line, they’re soldering, coating, packaging, and checking for quality. Whether you’re visiting a GE turbine plant in South Carolina, or a cable-modem factory in Shanghai, the thing you’ll notice is just how few people there actually are. It’s why, in the U.S., manufacturing output rises every year while manufacturing employment is essentially stagnant. It’s why it is becoming conventional wisdom that automation is destroying more manufacturing jobs than trade. And now we are seeing the prospect of dark factories, which can run without lights because there are no people in them, are starting to become a reality. The integration of A.I. into factories is one of the reasons Trump’s promise to bring back manufacturing employment is absurd. You’d think his treasury secretary would know something about that.

It goes far beyond manufacturing, of course. Programmatic advertising buying, Spotify’s recommendation engines, chatbots on customer service websites, Uber’s dispatching system—all of these are examples of A.I. doing the work that people used to do. …

Adding to Mnuchin’s lack of credibility on the topic of jobs and robots/AI, Matthew Rozsa’s March 28, 2017 article for Salon.com features a study from the US National Bureau of Economic Research (Note: Links have been removed),

A new study by the National Bureau of Economic Research shows that every fully autonomous robot added to an American factory has reduced employment by an average of 6.2 workers, according to a report by BuzzFeed. The study also found that for every fully autonomous robot per thousand workers, the employment rate dropped by 0.18 to 0.34 percentage points and wages fell by 0.25 to 0.5 percentage points.

I can’t help wondering if the US Secretary of the Treasury is so oblivious to what is going on in the workplace whether that’s representative of other top-tier officials such as the Secretary of Defense, Secretary of Labor, etc. What is going to happen to US research in fields such as robotics and AI?

I have two more questions, in future what happens to research which contradicts or makes a top tier Trump government official look foolish? Will it be suppressed?

You can find the report “Robots and Jobs: Evidence from US Labor Markets” by Daron Acemoglu and Pascual Restrepo. NBER (US National Bureau of Economic Research) WORKING PAPER SERIES (Working Paper 23285) released March 2017 here. The introduction featured some new information for me; the term ‘technological unemployment’ was introduced in 1930 by John Maynard Keynes.

Moving from a wholly US-centric view of AI

Naturally in a discussion about AI, it’s all US and the country considered its chief sceince rival, China, with a mention of its old rival, Russia. Europe did rate a mention, albeit as a totality. Having recently found out that Canadians were pioneers in a very important aspect of AI, machine-learning, I feel obliged to mention it. You can find more about Canadian AI efforts in my March 24, 2017 posting (scroll down about 40% of the way) where you’ll find a very brief history and mention of the funding for a newly launching, Pan-Canadian Artificial Intelligence Strategy.

If any of my readers have information about AI research efforts in other parts of the world, please feel free to write them up in the comments.

Movies and science, science, science (Part 2 of 2)

Part 1 concerned the soon-to-be-released movie, Hidden Figures and a film which has yet to start production, Photograph 51 (about Rosalind Franklin and the discovery of the double helix structure DNA [deoxyribonucleic acid]). Now for Part 2:

A matter of blood, Theranos, and Elizabeth Holmes

A few months ago, a friend asked me if I’d heard of Theranos. Given that I have featured various kinds of cutting edge diagnostic tests here, it was a fair enough question. Some  of my first questions to her were about the science. My friend had read about the situation in The Economist where the focus of the story (which I later read) was about venture capital. I got back to my friend and said that if they hadn’t published any scientific papers, I most likely would not have stumbled across them. Since then I’ve heard much more about Theranos but it seems there’s not much scientific information to be had from the company.

Reportedly, US film star Jennifer Lawrence is set to star, from a June 10, 2016 posting by Lainey (at Lainey Gossip; Note: A link has been removed),

Deadline reported yesterday [June 9, 2016] that Jennifer Lawrence will star in Adam McKay’s upcoming film about Elizabeth Holmes and Theranos. Elizabeth Holmes was basically the Jennifer Lawrence of Silicon Valley after inventing what she claimed to be a revolutionary blood testing system. Instead of submitting full vials of blood for limited testing, her product promised more efficiency and quicker results with just a pinprick. You can imagine how that would change the health care industry.

Last year, The Wall Street Journal investigated the viability of Theranos’s business plan, exposing major problems in the company’s infrastructure. Elizabeth Holmes went from being called the world’s youngest self-made female billionaire, the millennial in a turtleneck, to a possible fraud. It’s a fascinating story. …

In a July 16, 2016 article The Economist provides an update to the evolving Theranos/Holmes story,

FIRST they think you’re crazy, then they fight you, and then all of the sudden you change the world,” said Elizabeth Holmes as troubles mounted for her blood-testing startup, Theranos, last year. Things look ever less likely to go beyond the fighting stage.

On July 7th [2016] a government regulator, the Centres for Medicare and Medicaid Services, said Ms Holmes would be barred from owning or running a laboratory for two years. It will also revoke her company’s licence to operate one of two laboratories where it conducts tests. As The Economist went to press the firm was due to reply to a letter from Congress, which asked how, exactly, Theranos is going to handle the tens of thousands of patients who were given incorrect test results. Even so, Ms Holmes looks set to remain in position even as the situation deteriorates around a firm that once commanded a multi-billion-dollar valuation.

These may be some of the last twists in a story which will be turned into a Hollywood film by the director of “The Big Short”.

For anyone wondering how a movie could be made when the story has come to any kind of resolution, there’s this from a June 24, 2016 posting by David Bruggeman for his Pasco Phronesis blog (Note: Links have been removed),

Since last I wrote about a possible film about the medical device/testing company Theranos, a studio has successfully bid on the project.  Legendary Studios won an auction on the film rights, beating out 9 other offers on the project, which has Jennifer Lawrence attached to star as Theranos CEO Elizabeth Holmes.  Adam McKay would write the script and direct the project, duplicating his roles on the Oscar-nominated film The Big Short.  The film now has a preliminary title of Bad Blood.  It is certainly too early to tell if the Taylor Swift song of the same name will be used in the movie.

While getting a studio offer is important to the film getting produced, what is perhaps as interesting to our readers is that a book is connected to the film deal.  Two-time Pulitzer-prize winning writer John Carreyrou, who has written extensively on Theranos in The Wall Street Journal, will be writing a book that (presumably) serves as the basis for the script.  This follows the development arc for The Big Short, for which McKay shares an Adapted Screenplay Oscar (in addition to his nomination for directing the film)

So, are they going to wait until Holmes is either finally vindicated or vilified before going to film? Meanwhile, Holmes continues in a quest to save her company (from an Aug. 1, 2016 article for Fast Company by Christina Farr titled: Scientists Wanted Transparency From Theranos, But Got A Product Launch Instead (Note: A link has been removed),

Theranos once promised to revolutionize the blood testing industry. But its methodology remains secretive, despite calls for transparency from the scientific community. Now, it is facing federal investigations, private litigation, voided tests, and its CEO, Elizabeth Holmes, is banned from operating a lab for two years.

But all that was entirely glossed over today at the company’s much-awaited first presentation to the scientific community at the American Association for Clinical Chemistry’s conference in Philadelphia.

In an hour-long presentation (you can review the slides here), Holmes failed to discuss the fate of the company’s proprietary blood-testing technology, Edison, or address any of the controversy. Instead, she skipped right to pitching a new product, dubbed the MiniLab.

In fairness to Theranos, this was a positive step as the company did provide some internal data to show that the company could perform a small number of tests. But despite that, many took to social media to protest its failure to address and acknowledge its shortcomings before moving on to a new product.

“Clearly, the scientific and medical community was hoping for a data-driven discussion today, and instead got a new product announcement,” says John Torous, a psychiatrist and clinical informatics fellow at Harvard Medical School.

In an emailed response to Fast Company, a Theranos company spokesperson did not say whether components of Edison would be used in the miniLAB, but instead stressed that it’s one early iteration of the technology. “The miniLab is the latest iteration of the company’s testing platform and an evolution of Theranos’ technology,” they said.

Farr describes the MiniLab and notes that it is entering a competitive market,

The new product, the MiniLab, essentially takes equipment used in a standard lab and puts it in a single box. Holmes refers to this technique as “decentralizing the lab,” as in theory, clinicians could use this as an alternative to sending samples to a centralized facility and awaiting results. “Think of it as being a huge diagnostics lab that has been condensed down to the size of a microwave,” the company’s website explains.

..

But scientists are questioning whether the MiniLab technology is a breakthrough. The current market is already fairly saturated: Abbott’s iStat system, for instance, is a handheld device for clinicians to test patients for a plethora of common tests. Roche just received FDA [US Food and Drug Administration] clearance for its Cobas device, which can test for ailments like the flu and some strep infections in under 20 minutes. And Theranos competitors Quest and Labcorp already operate versions of this type of equipment in their own labs.

“I can’t imagine why they’re wasting their time,” says MIT-trained material scientist and biotech entrepreneur Kaveh Milaninia by phone. …

I recommend reading Farr’s article in its entirety as she provides more detail and analysis as to just how competitive the market Theranos proposes entering with its MiniLab actually is.

An Aug. 31, 2016 article by Lydia Ramsey for Slate.com the most recent update on the Theranos situation,

Theranos is withdrawing its bid for FDA approval of a diagnostic test for Zika that they announced earlier in August, according to a story in the Wall Street Journal.

Theranos confirmed to Business Insider that the test has been withdrawn, but said the company has plans to resubmit it.

John Carreyrou and Christopher Weaver report that an FDA inspection found that, as part of a study to validate the new test, the company had collected some data without a patient safety plan in place that was approved by an institutional review board.

“We hope that our decision to withdraw the Zika submission voluntarily is further evidence of our commitment to engage positively with the agency. We are confident in the Zika tests and will resubmit it,” Theranos vice president of regulatory and quality Dave Wurtz said in a statement emailed to Business Insider. Wurtz joined the company in July [2016].

Getting back to the point of my story at the beginning of this piece, it seems that Theranos and Elizabeth Holmes have not been as forthcoming with scientific data as is common in the biotech field. Interestingly, I read somewhere that the top 10 venture capitalists in the biotech field had not invested a penny in Theranos. The money had come from venture capitalists expert in other fields. (If you can confirm or know differently, please let me know in the comments section.)

In its favour, the company does appear to be attempting to address its shortcomings.

*ETA Oct. 6, 2016: Theranos is closing down some of its labs according to an Oct. 6, 2016 news item on phys.org,

Theranos, a onetime star Silicon Valley startup focused on health technology, is closing its consumer blood-testing facilities amid its struggles with US regulators.

The company, which has been seeking to disrupt the medical testing sector with new technology, said the closings will mean cutting some 340 jobs.

“After many months spent assessing our strengths and addressing our weaknesses, we have moved to structure our company around the model best aligned with our core values and mission,” company founder Elizabeth Holmes said in an open letter.

Theranos, which touts a new way of testing that uses far less blood and delivers faster results at much lower cost than traditional methods in US labs, has been under civil and criminal investigation over its claims.

Holmes said the company would focus on a so-called miniLab which can be commercialized with partners.

Things don’t look good.*

In any event, all these goings on should make for an interesting script writing challenge.

Bits and bobs of science and movies (The Man Who Knew Infinity, Ghostbusters, and Imagine Science Films)

The Man Who Knew Infinity had its debut at the 2015 Toronto International Film Festival. I haven’t seen it at any movie houses here (Vancouver, Canada) yet but a film trailer featuring its star, Dev Patel, was released in Feb. 2016,

Ramanujan must have been quite the mathematician, given the tenor of the times. Here’s more about the movie from its Wikipedia entry (Note: Links have been removed),

The Man Who Knew Infinity is a 2015 British biographical drama film based on the 1991 book of the same name by Robert Kanigel. The film stars Dev Patel as the real-life Srinivasa Ramanujan, a mathematician who after growing up poor in Madras, India, earns admittance to Cambridge University during World War I, where he becomes a pioneer in mathematical theories with the guidance of his professor, G. H. Hardy (played by Jeremy Irons despite Hardy being only 10 years older than Ramanujan).

Filming began in August 2014 at Trinity College, Cambridge.[4] The film had its world premiere as a gala presentation at the 2015 Toronto International Film Festival,[1][5] and was selected as the opening gala of the 2015 Zurich Film Festival.[6] It also played other film festivals including Singapore International Film Festival[7] and Dubai International Film Festival.[8]

Distinguished mathematicians Manjul Bhargava and Ken Ono are Associate Producers of the film.[9] Ono, the mathematics consultant, is a Guggenheim Fellow, and Bhargava is a winner of the Fields Medal.

Next up, Ghostbusters, the all woman edition. While it hasn’t become the blockbuster some were hoping for, I have some hope that it will become a quiet blockbuster over time. As I wait there is this information about how Ghostbuster: The All Woman Edition was grounded in real science. From a July 18, 2016 news item on phys.org,

Janet Conrad and Lindley Winslow, colleagues in the MIT [Massachusetts Institute of Technology] Department of Physics and researchers in MIT’s Lab for Nuclear Science, were key consultants for the all-female reboot of the classic 1984 supernatural comedy that is opening in theaters today. And the creative side of the STEM fields—science, technology, engineering, and mathematics—will be on full display.

A July 16, 2016 MIT news release, which originated the news item expands on the theme (Note: Links have been removed),

Kristin Wiig’s character, Erin Gilbert, a no-nonsense physicist at Columbia University, is all the more convincing because of Conrad’s toys. Her office features demos and other actual trappings from Conrad’s workspace: books, posters, and scientific models. She even created detailed academic papers and grant applications for use as desk props.

“I loved the original ‘Ghostbusters,’” says Conrad. “And I thought the switch to four women, the girl-power concept, was a great way to change it up for the reboot. Plus I love all of the stuff in my office. I was happy to have my books become stars.”

Conrad developed an affection for MIT while absorbing another piece of pop culture: “Doonesbury.” She remembers one cartoon strip featuring a girl doing Psets. She is discouraged until a robot comes to her door and beeps. All is right with the world again. The exchange made an impression. “Only at MIT do robots come by your door to cheer you up,” she thought.

Like her colleague, Winslow describes mainstream role models as powerful, particularly when fantasy elements in film and television enhance their childhood appeal. She, too, loved “Ghostbusters” as a kid. “I watched the original many times,” she recalls. “And my sister had a stuffed Slimer.”

Winslow jokes that she “probably put in too much time” helping with the remake. Indeed, Wired magazine recently detailed that: “In one scene in the movie, Wiig’s Gilbert stands in front of a lecture hall, speaking on challenges of reconciling quantum mechanics with Einstein’s gravity. On the whiteboards, behind her, a series of equations tells the same story: a self-contained narrative, written by Winslow and later transcribed on set, illustrating the failure of a once-promising physics theory called SU(5).”

Movie reviewers have been floored by the level of set detail. Also deserving of serious credit is James Maxwell, a postdoc at the Lab for Nuclear Science during the period he worked on “Ghostbusters.” He is now a staff scientist at Thomas Jefferson National Accelerator Facility in Newport News, Virginia.

Maxwell crafted realistic schematics of how proton packs, ghost traps, and other paranormal equipment might work. “I recalled myself as a kid, poring over the technical schematics of X-wings and Star Destroyers. I wanted to be sure that boys and especially girls of today could pore over my schematics, plug the components into Wikipedia, and find out about real tools that experimental physicists use to study the workings of the universe.”

He too hopes this behind-the-scenes MIT link with a Hollywood blockbuster will get people thinking. “I hope that it shows a little bit of the giddy side of science and of MIT; the laughs that can come with a spectacular experimental failure or an unexpected break-through.”

The movie depicts the worlds of science and engineering, as drawn from MIT, with remarkable conviction, says Maxwell. “So much of the feel of the movie, and to a great degree the personalities of the characters, is conveyed by the props,” he says.

Kate McKinnon’s character, Jillian Holtzmann, an eccentric engineer, is nearly inseparable from, as Maxwell says, “a mess of wires and magnets and lasers” — a pile of equipment replicated from his MIT lab. When she talks proton packs, her lines are drawn from his work.

Keep an eye out for treasures hidden in the props. For instance, Wiig’s character is the recipient of the Maria Goeppert Mayer “MGM Award” from the American Physical Society, which hangs on her office wall. Conrad and Winslow say the honor holds a special place in their hearts.

“We both think MGM was inspirational. She did amazing things at a time when it was tough for women to do anything in physics,” says Conrad. “She is one of our favorite women in physics,” adds Winslow. Clearly, some of the film’s props and scientific details reflect their personal predilections but Hollywood — and the nation — is also getting a real taste of MIT.

Finally and strictly speaking not a movie but it is an online magazine about science-based movies according to David Bruggeman’s Aug. 6, 2016 posting on his Pasco Phronesis blog (Note: Links have been removed),

LaboCine is an online film magazine from the people behind Imagine Science Films.  The films in each issue come from artists and scientists from around the world.  They are not restricted to documentary films, and mix live-action, animated and computer film styles.

The first issue of LaboCine is now online, so you can view the short films, which are organized around a common theme.  For August the theme is Model Organisms. …

You find the LaboCine magazine here and Imagine Science Films here. Btw, Raewyn Turner (NZ artist) has submitted our filmpoem, Steep (1) : A digital poetry of gold nanoparticles to the 9th Imagine Science Festival to be held Oct. 14-21, 2016 in New York City.

And that is it!

Here’s Part 1 for those who missed it.

Are Canadians really trying to recreate Silicon Valley in Canada?

As I recall it’s Robbie Burns who coined the phrase, ‘the gift to see ourselves as others see us’, and it’s the Globe and Mail newspaper in its May 17, 2013 article (Jason Kenney visits California to lure tech workers north) which provides that perspective in a quote about Minister of Immigration, Jason Kenney’s current  tour promoting Canada’s special Startup Visa,

“The Canadian perspective is they would love to re-create Silicon Valley in Canada,” said Irene Bloemraad, a professor who chairs the Canadian studies program at UC Berkeley. “And they recognize that under the current immigration system in the United States … there are people who are having a hard time getting permanent legal status.”

Anirudh Bhattacharyya writing for the Hindustan Times about Kenney’s tour and this latest effort to attract entrepreneurs to Canada notes in a May 16, 2013 article,

As Canada’s minister for citizenship, immigration and multiculturalism Jason Kenney heads to California’s Silicon Valley for four days, pushing the country’s new Startup Visa programme, he will make an appearance at TiECon 2013, the annual conference of The Indus Entrepreneurs [TIE], dominated by tech pioneers of Indian origin.

Minister Kenney will arrive in Silicon Valley on Friday [May 17, 2013], and will even be present at a Canadian government booth at the Santa Clara convention venue for TiECon, as part of an attempt to poach entrepreneurial talent in the tech sector away from the United States.

In an interview with the Hindustan Times, the minister said, “I think it’s no secret that many of the bright young people (in America) on short term work permits, are of Asian origin and more specifically of Indian origin.”

Canada’s Startup Visa program is similar to other efforts in Australia and the UK and it traces its own origins to a US initiative, from the Bhattacharyya article,

Ironically, the idea for the visa originated with the Canadian venture capital industry observing movement in the US Congress in recent years to create an American startup visa. That effort has yet to succeed. The industry then promoted the concept in Canada.

It’s not all roses and sunshine for entrepreneurs who wish to come to Canada although there is one major upside unique to the Canadian effort according to CICS Immigration Consulting’s May 17, 2013 posting on their website,

Citizenship and Immigration Canada (CIC) hopes to capitalize on the frustration tech companies in the U.S. are feeling over immigration restrictions on foreign technology workers and encourage them to relocate to and invest in Canada.

The eventual goal is to help foster the development of a Canadian equivalent to Silicon Valley.

One challenge that CIC faces in this mission is the country’s top marginal income tax rate, which is significantly higher than that of the U.S. A Canadian entrepreneur can look forward to paying about 50 percent of their income to the government if they succeed in joining the top bracket of income earners. [emphasis mine]

Compensating for this disadvantage, the federal government is offering a perk that no other advanced economy offers foreign entrepreneurs: permanent residency status. [emphasis mine]

I suppose this is one way of developing an entrepreneurial and innovative culture in Canada but it seems to me that if other conditions (financing, willingness to take risks, appropriate governmental regulations, etc.) are not met, this may cause yet more problems.

As to whether or not creating a ‘Silicon Valley’ in Canada is possible or even desirable, I don’t know. There is only one Louvre, one Terra Cotta army, one Borobudur, one Stonehenge, one Mount Olympus, one Grand Canyon, one Guggenheim, etc. Of course, there are other art museums, other funerary displays, and other wonders but there is always the one which holds precedence and retains its grip on the imagination in a way the others do not. Canadians can try to copy the US’s Silicon Valley but if our effort is to be successful, we must find a way to put our own stamp on it and we need to recognize that it may always stand in the shadow of its parent.